English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this work, we propose an approach to determine the dosages of antithyroidagents to treat hyperthyroid patients. Instead of relying on a trial-and-errorapproach as it is commonly done in clinical practice, we suggest to determinethe dosages by means of a model predictive control (MPC) scheme. To this end,we extend a mathematical model of the pituitary-thyroid feedback loop such thatthe intake of methimazole, a common antithyroid agent, can be considered. Basedon this extension, we develop an MPC scheme to determine suitable dosages. Innumerical simulations, we consider scenarios in which (i) patients are affectedby Graves' disease and take the medication orally, (ii) patients areadditionally affected by high intrathyroidal iodide concentrations and take themedication orally and, (iii) patients suffering from a life-threateningthyrotoxicosis, in which the medication is usually given intravenously. Ourresults suggest that determining the medication dosages by means of an MPCscheme is a promising alternative to the currently applied trial-and-errorapproach.

Treating Hyperthyroidism: Model Predictive Control for the Prescription of Antithyroid Agents